Zobrazeno 1 - 10
of 16 976
pro vyhledávání: '"lidar point clouds"'
3D perception in LiDAR point clouds is crucial for a self-driving vehicle to properly act in 3D environment. However, manually labeling point clouds is hard and costly. There has been a growing interest in self-supervised pre-training of 3D perceptio
Externí odkaz:
http://arxiv.org/abs/2409.06827
3D single object tracking (SOT) methods based on appearance matching has long suffered from insufficient appearance information incurred by incomplete, textureless and semantically deficient LiDAR point clouds. While motion paradigm exploits motion c
Externí odkaz:
http://arxiv.org/abs/2407.05238
The rotation robustness property has drawn much attention to point cloud analysis, whereas it still poses a critical challenge in 3D object detection. When subjected to arbitrary rotation, most existing detectors fail to produce expected outputs due
Externí odkaz:
http://arxiv.org/abs/2408.15643
Human motion prediction is crucial for human-centric multimedia understanding and interacting. Current methods typically rely on ground truth human poses as observed input, which is not practical for real-world scenarios where only raw visual sensor
Externí odkaz:
http://arxiv.org/abs/2408.08202
Although LiDAR semantic segmentation advances rapidly, state-of-the-art methods often incorporate specifically designed inductive bias derived from benchmarks originating from mechanical spinning LiDAR. This can limit model generalizability to other
Externí odkaz:
http://arxiv.org/abs/2407.11569
Autor:
Han, Zeyu, Jiang, Junkai, Ding, Xiaokang, Meng, Qingwen, Xu, Shaobing, He, Lei, Wang, Jianqiang
The 4D millimeter-wave (mmWave) radar, with its robustness in extreme environments, extensive detection range, and capabilities for measuring velocity and elevation, has demonstrated significant potential for enhancing the perception abilities of aut
Externí odkaz:
http://arxiv.org/abs/2405.05131
Autor:
Piroli, Aldi, Dallabetta, Vinzenz, Kopp, Johannes, Walessa, Marc, Meissner, Daniel, Dietmayer, Klaus
Adverse weather conditions can severely affect the performance of LiDAR sensors by introducing unwanted noise in the measurements. Therefore, differentiating between noise and valid points is crucial for the reliable use of these sensors. Current app
Externí odkaz:
http://arxiv.org/abs/2406.09906
Autor:
Tian, Zeyu1,2 (AUTHOR) fangxiaohui@hljit.edu.cn, Fang, Yong1 (AUTHOR) yong.fang@vip.sina.com, Fang, Xiaohui2 (AUTHOR) mayan@hljit.edu.cn, Ma, Yan2 (AUTHOR), Li, Han3 (AUTHOR) 840163997@hrbeu.edu.cn
Publikováno v:
Sensors (14248220). Dec2024, Vol. 24 Issue 23, p7503. 23p.
Autor:
Zhao, Zhenfeng1,2,3 (AUTHOR) 20181101012@stu.kust.edu.cn, Gan, Shu1 (AUTHOR) gs@kust.edu.cn, Xiao, Bo4 (AUTHOR) 240016@ynnu.edu.cn, Wang, Xinpeng5,6 (AUTHOR) xpwang3@gzu.edu.cn, Liu, Chong2 (AUTHOR) liuchongwhu@whu.edu.cn
Publikováno v:
Remote Sensing. Oct2024, Vol. 16 Issue 19, p3722. 21p.
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